Product Introduction Product Overview The DEEPX DX-M1 M.2 module brings server-grade AI inference directly to edge devices. The DX-M1 delivers 25 TOPS of performance with only 2W to 5W of power, offering 20 times the performance efficiency (FPS/W) of a GPGPU while maintaining GPU-level AI accuracy. Detailed specifications Instructions for use Install Connect to the M.2 interface of the RK3588, turn on the power, and confirm whether the DX-M1 PCIe accelerator card can be recognized. root@firefly:/home/firefly# lspci 0004:40:00.0 PCI bridge: Rockchip Electronics Co., Ltd Device 3588 (rev 01) 0004:41:00.0 Processing accelerators: Device 1ff4:0000 (rev 01) Deployment Environment Download code git clone --recurse-submodules https://github.com/DEEPX-AI/dx-all-suite.git Compile and install drivers # Before compiling, you need to install Linux Headers on your device. Please refer to https://wiki.t-firefly.com/en/Firefly-Linux-Guide/first_use.html#linux-headers cd /dx-all-suite/dx-runtime/dx_rt_npu_linux_driver/modules/ ./build.sh -d m1 ./build.sh -d m1 -c install # After installation, you can see dxrt_driver using lsmod. lsmod Install dx_rt cd ./dx-all-suite/dx-runtime/dx_rt ./install.sh --all ./build.sh --install /usr/local sudo cp ./service/dxrt.service /etc/systemd/system sudo systemctl start dxrt.service sudo systemctl enable dxrt.service cd python_package pip3 install . reboot # After installation, you can check the DX-M1 status using commands. dxrt-cli -s Upgrade Firmware # The firmware on the DX-M1 may be incompatible with the current SDK. You can update the firmware corresponding to the SDK first. cd ~/dx-all-suite/dx-runtime/dx_fw dxrt-cli -u ./m1/latest/mdot2/fw.bin Test # Download the pre-compiled model from https://developer.deepx.ai/article/modelzoo/ ,This test uses the YoloV5S model # run_model is benchmark tool. run_model -m ./YoloV5S.dxnn -b -l 100 -v More Information github: https://github.com/DEEPX-AI/